Sr. Deep Learning Engineer (Remote)

We are seeking an experienced Sr/Ssr Deep Learning Engineer with a focus on Computer Vision to join our dynamic and growing team in the sports streaming industry. This is a fully remote opportunity, offering flexibility while collaborating with a global team to enhance sports data-driven solutions. You will play a key role in processing and analyzing sports data, particularly from basketball and soccer, to create innovative AI-powered streaming experiences.

We are a leading streaming company specializing in sports data, with a mission to revolutionize the sports viewing experience through AI-driven technologies. Our focus is on creating cutting-edge solutions for basketball and soccer and pushing the boundaries of what's possible with data.

As a Deep Learning Engineer (Computer Vision), you will work on:

• Preprocessing sports data (e.g., basketball and soccer) for training computer vision models.
• Performing quality assurance (QA) on model outputs to ensure high accuracy and reliability.
• Designing and running experiments to improve model performance in real-world applications.
• Collaborating with international teams to develop and deploy advanced computer vision solutions.

• Prepare and preprocess sports data for training deep learning models.
• Ensure quality of model outputs through rigorous QA processes.
• Design and conduct experiments to enhance model performance.
• Collaborate with global teams to create and implement innovative solutions.
• Develop and optimize machine learning models for real-world use.

• Strong understanding of deep learning principles, specifically for computer vision.
• Proficiency in Python programming with clean, efficient code.
• Hands-on experience with OpenCV, scikit-image, or similar computer vision libraries.
• Familiarity with deep learning frameworks: PyTorch, TensorFlow, or Keras.
• Expertise in key computer vision tasks like object detection, image segmentation, and tracking.
• Ability to work effectively in a remote, international team environment, accommodating time zone differences.

• Experience with MMDetection and OpenMMLab ecosystem.
• Familiarity with CI/CD tools such as GitHub Actions or Jenkins.
• A passion for sports analytics, especially basketball or soccer dynamics.